@inproceedings{14410,
  abstract     = {This paper focuses on the implementation details of the baseline methods and a recent lightweight conditional model extrapolation algorithm LIMES [5] for streaming data under class-prior shift. LIMES achieves superior performance over the baseline methods, especially concerning the minimum-across-day accuracy, which is important for the users of the system. In this work, the key measures to facilitate reproducibility and enhance the credibility of the results are described.},
  author       = {Tomaszewska, Paulina and Lampert, Christoph},
  booktitle    = {International Workshop on Reproducible Research in Pattern Recognition},
  isbn         = {9783031407727},
  issn         = {1611-3349},
  location     = {Montreal, Canada},
  pages        = {67--73},
  publisher    = {Springer Nature},
  title        = {{On the implementation of baselines and lightweight conditional model extrapolation (LIMES) under class-prior shift}},
  doi          = {10.1007/978-3-031-40773-4_6},
  volume       = {14068},
  year         = {2023},
}